Presentation
Secure Run-Time Hardware Trojan Detection using Lightweight Analytical Models
DescriptionThere has been substantial research into the detection of hardware Trojans during the pre-deployment stages of silicon design. In this work, we propose a hardware Trojan detection methodology based on analytical modeling that is based on the inherent microarchitecturally-independent characteristics of the application. By comparing predicted values to actual hardware events, one can quickly check for unexpected application slowdowns that are the key signatures of many hardware Trojans. The proposed methodology achieves a higher true positive rate compared to prior works. The detector incurs no runtime performance penalty and only adds a negligible power overhead of 0.005%.
Event Type
Work-in-Progress Poster
TimeTuesday, July 11th6:00pm - 7:00pm PDT
LocationLevel 2 Lobby
AI
Autonomous Systems
Cloud
Design
EDA
Embedded Systems
RISC-V
Security